The recent pandemic has proven to be a saddening and unfortunate foe to the lives of many of us. What started on a very small scale in Wuhan, China back in December of 2019 has become a tyrant upon the globe, restricting the vast majority of people in many ways.

Unfortunately, in times like these, data can be rather unclear and confusing to interpret. This leads to a surge of misinformation that eventually leads to misinformed action. That is the last thing that we all want as a society. This report shares some simple information in a conscise manner, to help everyone reading a sense of what all of this looks like.

I want to first show you a map of the United States and the relative hotspots of confirmed cases that we have as shown by Anisa Dhana. This will provide some context as we zoom in to see our home state of Michigan. If we look at our state of Michigan more closely, we see the approximate number of confirmed cases based on the relative regions.

Now if we want to see a more specific and defined number per county, we can also look at this.

We can see that the most affected portion of the entire state of Michigan is, by far, Wayne County. This is followed by Oakland. As you guys live there, you know that Detroit is in Wayne County. I find it interesting that the areas that simultaneously have an extreme poverty rate and a high population density within the state are those that are the most significantly affected.

I want us to take a bird’s eye view of the basic data that we have regarding COVID-19. Considering it’s saddening and oppressive nature, this stuff elicits a mass of confusion and chaos in everyone’s lives. People interpret data for others and listen to so many different sources and their opinions. The graphs below are made to allow you to make your own judgements on the state of our planet. Personally, I find it both frightening and encouraging. No matter what happens though, I know we’ll make it to the other side.

These graphics and animations were generated using COVID-19 data from the John Hopkins University Center for Systems Science and Engineering [JHU_CSSE].

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